agentsvc-mcp

vin_decode

Decode a 17-character VIN into make, model, year, trim, engine, drive, and plant data; validates format and check digit via NHTSA vPIC.

Instructions

VIN Decoder — Decode a 17-character vehicle identification number with NHTSA vPIC: make, model, model year, trim, body, doors, engine (cylinders, displacement, hp, fuel, electrification), drive, transmission, manufacturer and plant. Validates format and the check digit (mandatory for North American VINs). Best coverage for vehicles sold in the US. Params: vin (required). Cost: $0.0035 USDC per call. Latency p99: 2000ms.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "vin": "<vin>"
    },
    "name": "vin_decode"
  }
}

Input Schema

Name	Required	Description	Default
`vin`	Yes	17-character VIN

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Oct 21, 2026

TDQS

A4.4/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden and does so well: it discloses the data source, the validation behavior (format plus mandatory check digit for North American VINs), the coverage limitation, the per-call cost ($0.0035 USDC), and p99 latency (2000ms). These are exactly the operational facts an agent needs before invoking a paid, network-backed call.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core action, then the returned fields, then validation, coverage, params, cost, and latency in a compact structured run. The field enumeration is long but each item is informative for an agent deciding whether the tool returns what it needs; no sentence is pure filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema and no annotations, yet the description enumerates the decoded fields (make, model, year, trim, body, doors, engine specs, drive, transmission, manufacturer, plant), effectively documenting the return payload, and it covers cost, latency, and validation. Nothing an agent needs to call it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% and the single parameter is already documented as '17-character VIN'. The description only restates 'vin (required)', adding no format, syntax, or normalization guidance beyond the schema, so the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource ('Decode a 17-character vehicle identification number') and names the underlying source (NHTSA vPIC). No sibling tool overlaps this function, and the description immediately distinguishes it as a VIN-specific decoder.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives clear context for when it works well ('Best coverage for vehicles sold in the US') and notes the check-digit requirement for North American VINs, which implies limits for non-NA VINs. It does not name an alternative tool, but no sibling performs a comparable decode, so this is a minor gap.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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